yeast

<p>A dataset containing measurements of growth of yeast in a culture. The variables are as follows:</p>

datasets

Designed to support the visualization, numerical computation,
qualitative analysis, model-data fusion, and stochastic simulation for
autonomous systems of differential equations. Euler and Runge-Kutta methods
are implemented, along with tools to visualize the two-dimensional
phaseplane. Likelihood surfaces and a simple Markov Chain Monte Carlo
parameter estimator can be used for model-data fusion of differential
equations and empirical models. The Euler-Maruyama method is provided for
simulation of stochastic differential equations. The package was originally
written for internal use to support teaching by Zobitz, and refined to
support the text "Exploring modeling with data and differential equations
using R" by John Zobitz (2021) <https://jmzobitz.github.io/ModelingWithR/index.html>.

John Zobitz

demodelr

Simulating Differential Equations with Data

yeast function

<p>A data frame with 7 rows and 2 variables</p>

yeast: Measured Sacchromyces data (yeast) from Gause 1932 "Experimental studies on the struggle for coexistence"

Description

Usage

Arguments

Format

Details